RT info:eu-repo/semantics/article
T1 Modeling the international roughness index performance on semi-rigid pavements in single carriageway roads
A1 Pérez Acebo, Heriberto
A1 Gonzalo Orden, Hernán
A1 Findley, Daniel J.
A1 Rojí, Eduardo
K1 International Roughness Index
K1 IRI
K1 Pavement performance model
K1 Semi-rigid pavement
K1 Pavement management system
K1 Deterministic model
K1 Pavement roughness
K1 Deterioration model, treated base
K1 Pavement deterioration
K1 Pavimentos
K1 Pavements
K1 Carreteras
K1 Roads
AB Pavement deterioration models are a vital feature in any pavement management system since they are capable of predicting the evolution of pavement characteristics. Pavement roughness is measured by most of the highway administrations due to its relation to comfort and safety, generally by means of the International Roughness Index (IRI). The Regional Government of Biscay (Spain) has collected IRI values since 2000 on its road network. Although many models have been developed for flexible pavements, very few have been proposed for semi-rigid pavements. The paper aims to develop IRI prediction models for semi-rigid pavements in single-carriageway roads. Considering the high quantity of available information in the database, deterministic models were selected. Due to the importance of the pavement structure in IRI evolution observed in flexible models, only segments with completely known pavement details were employed, i.e., a section where the complete structure is known: materials and thickness of existing layers above the subgrade. The pavement age, as precise as practical, and the accumulated total traffic and heavy traffic through the section were identified as roughness accelerating factors. Conversely, the materials used in base and subbase layers, their thickness, and the total thickness of bituminous layers were observed as degradation reducing factors. Possible treated base and subbase materials included in the model were soil–cement, gravel-cement, and gravel and slag. The obtained model achieved a determination coefficient (R2) of 0.569. Additionally, the bituminous material of the surface layer was verified as an affecting factor too, which can be introduced to improve the model’s accuracy. Possible surface layer materials included dense (D) and semi-dense (S) asphalt concrete, with a maximum aggregate diameter of 16 and 22 mm, discontinuous mixing (BBTM 11A) and porous asphalt (PA 11). The additional model achieved a higher determination coefficient (0.645) and, hence, a more accurate IRI prediction resulted.
PB Elsevier
SN 0950-0618
YR 2021
FD 2021-02
LK http://hdl.handle.net/10259/9868
UL http://hdl.handle.net/10259/9868
LA eng
NO This work was supported by the Diputación Foral de Bizkaia, Departamento de Obras Públicas y Transportes [Agreement on 25/06/2014]; Erasmus + KA107 – 2017 project for mobilities from UPV/EHU (Spain) to universities in United States, Morocco, Russian Federation and Kazakhstan; and Erasmus + KA107 – 2015 project for mobility from universities in the USA, Canada, South Korea and Russia to the UPV/EHU (Spain).
DS Repositorio Institucional de la Universidad de Burgos
RD 21-ene-2025